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20242026
most citedTowards Edge General Intelligence via Large Language Models: Opportunities and Challenges

26 citations · 74 across the 25 of their papers we have counts for

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10 papers · 1 filter

cs.IR2026

Agents as Knowledge Integrator and Utilizer in Multimodal Recommendation

Jinfeng Xu, Zheyu Chen, Shuo Yang +9

Online platforms increasingly rely on multimodal recommender systems to rank products, media, and other Web content. Existing methods usually inject visual and textual features int…

cs.IR2026

Neural Tree Collaborative Filtering: Rethinking Graph Collaborative Filtering as Tree Collaborative Filtering with Curvature-Aware Propagation Depth

Jinfeng Xu, Zheyu Chen, Ziyue Peng +5

Graph Collaborative Filtering (GCF) has become the dominant paradigm in modern recommender systems by modeling user-item interactions as a bipartite graph and propagating embedding…

cs.IR2026

One Graph, Multiple Gains: Single High-Quality Item-Item Graph for Multimodal Recommendation

Jinfeng Xu, Zheyu Chen, Ziyue Peng +6

Multimodal recommendation leverages item multimodal features alongside collaborative signals to capture user preferences. While item-item graphs have become a key building block in…

cs.CL2026

LATTE: Forecasting Peer Anchored Preference Trajectories for Personalized LLM Generation

Jinze Li, Xiaoyan Yang, Shuo Yang +5

Personalized generation with frozen large language models requires a conditioning signal that is both compact and current. Existing personalization methods typically retrieve or su…

cs.RO2026

TapSampling: Inference-Time Sampling with a Task-Progress-Understanding Verifier for Robotic Manipulation

Sizhe Zhao, Shengping Zhang, Shuo Yang +3

Existing embodied control research demonstrates remarkable performance improvements by scaling training data and model size. We instead explore inference-time strategy as an altern…

cs.CL2026

Beyond the Target: From Imitation to Collaboration in Speculative Decoding

Jinze Li, Yixing Xu, Guanchen Li +7

Speculative decoding (SPD) accelerates large language model (LLM) inference by letting a smaller draft model propose multiple future tokens that are verified in parallel by a large…

cs.AI2026

Belief-Guided Inference Control for Large Language Model Services via Verifiable Observations

Wenhao Yuan, Chenchen Lin, Jian Chen +3

In black-box large language model (LLM) services, response reliability is often only partially observable at decision time, while stronger inference pathways incur substantial comp…

cs.CL2026

OCR-Memory: Optical Context Retrieval for Long-Horizon Agent Memory

Jinze Li, Yang Zhang, Xin Yang +5

Autonomous LLM agents increasingly operate in long-horizon, interactive settings where success depends on reusing experience accumulated over extended histories. However, existing…

cs.IR2026

Well Begun is Half Done: Training-Free and Model-Agnostic Semantically Guaranteed User Representation Initialization for Multimodal Recommendation

Jinfeng Xu, Zheyu Chen, Shuo Yang +6

Recent advancements in multimodal recommendations, which leverage diverse modality information to mitigate data sparsity and improve recommendation accuracy, have gained significan…

cs.IR2026

CAMMSR: Category-Guided Attentive Mixture of Experts for Multimodal Sequential Recommendation

Jinfeng Xu, Zheyu Chen, Shuo Yang +6

The explosion of multimedia data in information-rich environments has intensified the challenges of personalized content discovery, positioning recommendation systems as an essenti…